Exploit Social Distancing in Construction Scheduling: Visualize and Optimize Space–Time–Workforce Tradeoff
Publication: Journal of Management in Engineering
Volume 38, Issue 4
Abstract
The COVID pandemic has given rise to the necessity of social distancing regulations, which has brought the importance of workspace management on the construction site to an unprecedented level. Understanding and visualizing the interaction and tradeoff among space, time, and workforce is critical for construction managers to schedule and deliver projects on time. Therefore, the objectives of this research are to investigate how the critical path method (CPM) and Takt-time planning methods utilize space, time, and workforce differently, develop a tool to visualize the space–time–workforce interactions, and investigate the space–time–workforce tradeoff based on different managers’ preferences. This research selected a high-rise office building project and collected 889 sets of productivity data of five specialty trades. The research built a simulation model to investigate productivity and project performance under 267 scenarios of different combinations of the three resources. A dynamic tool was then developed to visualize workspace, time, and workforce interactions. Finally, a Choquet integral–based evaluation and decision tool was developed. The simulation results show that the Takt-time planning method can reduce up to 80% of workspace overlap compared with the actual production plan with less than 20% of duration extension. The contributions to the body of knowledge are (1) creating a visual framework for managers to understand the interaction and tradeoff among space, time, and workforce quickly and accurately, and (2) developing an innovative Choquet integral approach for managers to evaluate planning strategies according to project preferences. The framework and analysis method can be adapted to other construction projects to assist managers to visualize and optimize the space–time–workforce tradeoff under uncertain project drivers.
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Data Availability Statement
Some or all data, models, or code generated or used during the study are available from the corresponding author by request.
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Journal of Management in Engineering
Volume 38 • Issue 4 • July 2022
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© 2022 American Society of Civil Engineers.
History
Received: Jul 6, 2021
Accepted: Jan 5, 2022
Published online: Apr 5, 2022
Published in print: Jul 1, 2022
Discussion open until: Sep 5, 2022
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